OECD Occasional Paper: April 2014 February 2015

Transcription

1 TFFS 15/06 Meeting of Inter-Agency Task Force on Finance Statistics UNCTAD Headquarters, Geneva, Switzerland March 12 13, 2015 OECD Occasional Paper: April 2014 February 2015 Prepared by the OECD

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5 3 A. OECD Development Cooperation Directorate 1. Official credits Data on official bilateral lending for 2011 (revisions) and 2012 (new data), were provided to the JEDH in SDMX format in July The OECD plans to submit data on 2013 bilateral loans in June For further information, please contact Ms. Yasmin Ahmad 2. Modernising the DAC s Development Finance Statistics The OECD/DAC statistics on development finance are a global public good that inform policy choices, promote transparency and foster accountability. Following the mandate that DAC members adopted at their High Level Meeting (HLM) in 2012, work was undertaken to modernise the DAC s statistical system, measures and standards to ensure data integrity and comparability on development finance and create the right incentive mechanisms for effective resource mobilisation. Official development assistance (ODA) will remain a crucial part of development cooperation in implementing the post 2015 agenda. Modernising the reporting of concessional loans in DAC statistics While most of ODA is provided in the form of grants, concessional loans are an important part of this measure. Concessional loans help mobilise more resources for countries with limited or no access to international capital markets, including many low-income countries. In recent years, some DAC donors have been scaling up their lending programmes. Under the present reporting rules, to be recognised as concessional and reportable as ODA, a loan must have a grant element of at least 25%, calculated at a 10% discount rate and be concessional in character. Members different interpretations of the unclear concessional in character criterion of the ODA definition, led to the modernisation of reporting of concessional loans to make it easier to compare the effort involved with that of providing grants. At present, concessional loans are counted in DAC statistics on a cash flow basis, as positive when loans are extended and as negative when loans are repaid. Over time, the net effect of a loan if fully repaid is zero. To address the weakness of the current system, the DAC agreed to introduce a grant equivalent system for the purpose of calculating ODA figures. Under this new system, greater credit, in terms of the amount of ODA scored, is attributed to grants compared to loans. In the case of loans, more concessional loans will earn greater ODA credit than less concessional loans. The donor effort in providing a loan consists both of the funding cost of the loan and the risk associated with it. Lending to poorer countries involves greater donor effort than lending to richer countries, thus the DAC has agreed to assess concessionality based on differentiated discount rates. These rates will consist of a base factor, i.e. the IMF discount rate (currently 5%), plus an adjustment factor of 1% for UMICs, 2% for LMICs and 4% for LDCs and other LICs. In order to count as ODA in the new system and to ensure that loans to LDCs and other LICs are provided at highly concessional terms, only loans with a grant element of at least 45% will be reportable as ODA. Loans to LMICs need to have a grant element of at least 15%, and those to UMICs of at least 10%.

6 4 A higher discount rate for LDCs and other LICs, combined with a grant equivalent method whereby higher concessionality results in more ODA being reportable, should incentivise lending on highly concessional terms to LDCs and other LICs, and thereby to help concentrate the available ODA resources more on the poorest countries, a policy that members support. Loans, whose terms are not consistent with the IMF Debt Limits Policy and/or the World Bank s Non-Concessional Borrowing Policy will not be reportable as ODA. The main objective of ODA will still be the promotion of economic development and welfare of developing countries. The modernisation of concessionality in DAC statistics will become effective for ODA from 2018 (for which reporting will take place in early 2019). However, reporting will begin from ODA in 2015 (i.e. in reports issued from early 2016) to 2017 using both the new and the current (2013) system. ODA figures will continue to be calculated, reported and published on a cash flow basis in a fully transparent manner. The discount rates and the grant element thresholds under the new system will need to be regularly reviewed and possibly adjusted (e.g. in particular following any change to the IMF rate), to reflect changes in borrowing costs, emerging experience with risk (for example as reflected in default rates) and any need for further incentives for countries most in need. Finally, the cost of risk should not be double counted. Changing the measurement system from net flows to risk-adjusted grant equivalents will therefore also change the basis on which debt relief of ODA loans is reported. Therefore, the rules on reporting ODA debt relief will need to be updated to rule out double counting, bearing in mind the past need to encourage debt relief initiatives such as HIPC and MDRI. A new measure Total Official Support for Sustainable Development As the development agenda is becoming broader, it is important to recognise and further incentivise efforts made beyond ODA. The DAC has agreed to develop a new statistical measure, Total official support for sustainable development (TOSD) to complement ODA. This new measure will potentially cover all resource flows extended from official sources to developing countries and multilateral institutions that support sustainable development. Data on resources that are mobilised by official interventions from the private sector using leveraging instruments such as guarantees will also be collected. In developing this new measure, the DAC will consult broadly with developing countries, international institutions, other providers of development co-operation and stakeholders on the scope, definition and statistical features of the measure, with the aim to contribute to a more global monitoring mechanism. The parameters of TOSD will be clarified once final shape of the post-2015 agenda has been agreed. For further information, please contact Ms. Yasmin Ahmad (yasmin.ahmad@oecd.org).

7 5 3. Non-ODA Flows The OECD Development Cooperation Directorate (DCD) is also implementing a specific workstream to improve the coverage and policy relevance of DAC statistics beyond ODA 1. This work feeds into the broader work to develop a more comprehensive statistical framework for external development finance post Building on in-depth analyses on development finance providers portfolios and reporting, it includes: Efforts to modernise the DAC statistical framework (e.g. classification by types of finance) to better reflect the current development finance landscape, especially with regard to private sector instruments used in development finance; Methodological work to measure amounts mobilised from the private sector by development finance interventions (e.g. guarantees, syndicated loans and shares in collective investment vehicles) in DAC statistics; Ongoing tests to explore the feasibility to derive DAC statistics on export credits and international direct investments from other OECD bodies data systems, i.e. Export Credit Group and Working Group on International Investment Statistics databases respectively; Collaboration with other major data providers to improve the DAC picture of total developing countries resource inflows, including remittances (World Bank statistics) and private philanthropy beyond the Bill and Melinda Gates Foundation (US Foundation Center s statistics). B. OECD Statistics Directorate 1. Quarterly Public Sector Debt Statistics All OECD countries plus Colombia, Latvia and Russia, which are OECD accession countries, regularly provide the OECD/WB/IMF with detailed data on Public Sector Debt (PSD). Korea and Switzerland only report annual data, and Japan and Turkey complete the PSD questionnaire with nonconsolidated data. Since January 2015, only six countries are not following the S 2008 methodology. Twenty-nine OECD and accession countries report PSD data for the general government sector, thirty-five for the central government sector, and only six countries out of thirtyseven can provide data on the total public sector. Concerning the instrument coverage, progress is limited, especially on the reporting of other accounts payable and insurance, pension and standardised guarantee schemes data, as well as on the residual maturity breakdown. In 2015, particular attention will be devoted to improving the instrument coverage across OECD countries. On the valuation issue, the QPSD initiative requests nominal values for all debt instruments and market values for debt securities. However, different valuations are reported by OECD countries (face value, nominal value, market value, book value and present value), which hamper international comparability. For further details on the status of the QPSD data collection, please see table 1 in annex. Data in national currency, US dollars, and as a percentage of gross domestic product (GDP) up to the third quarter of 2014, are available on the OECD data warehouse OECD.Stat ( and on the World Bank website ( 1

8 6 In the coming weeks, Public Sector Debt data will be presented in a more transparent way on both websites. On the OECD data warehouse, OECD and accession countries will be classified in four categories D1 through D4, depending on debt instruments reported in the PSD questionnaire. These will range from a narrow definition including only debt securities and loans (D1) to a fully comprehensive definition covering all six debt instruments (D4) as defined in the Public Sector Debt Guide for User and Compilers and the S 2008 Manual. To build this classification, it was necessary to investigate and clarify the distinction between true zero and unavailable data. To this end, a quality survey has been sent to all countries. Please see the preliminary results of the survey in table 2 in annex. For further information, please contact Ms. Isabelle Ynesta (Isabelle.ynesta@oecd.org). 2. General government net debt measures At the March 2014 meeting of the Task Force on Finance Statistics (TFFS), member agencies agreed to include the preparation of a paper on general government net debt as part of the TFFS work program. The OECD and the IMF jointly worked on this paper, which first explains the need for a net debt measure; second, presents the definition of net debt as encompassed in the 2011 Public Sector Debt Statistics: Guide for Compilers and Users (PSDS Guide) as well as some alternative measures; third discusses the limitations of net debt; and fourth provides an overview of the availability of general government net debt data. The paper closes with some conclusions and a possible way forward. For further information, please contact M. Jorrit Zwijnenburg (Jorrit.ZWIJNENBURG@oecd.org) or Ms. Isabelle Ynesta (Isabelle.ynesta@oecd.org). 3. Pensions The OECD is continuing the development of a new supplementary table on household retirement resources. This table will contain the assets of households as the counterparty to all pension liabilities recorded in the core accounts and in Supplementary Table As part of a more general document on the recording and measurement of pension entitlements, the new table will also be presented at the next IMF Government Finance Statistics Advisory Committee meeting in March 2015, where the OECD will be looking to obtain feedback on various issues related to the recording and measurement of pension schemes. In order to advance the analytical thinking on pension liabilities, the OECD Directorate for Employment, Labour and Social Affairs (ELS) may publish a policy brief on the concept of implicit public pension debt. To inform this work, ELS is currently developing estimates of implicit public pension debt in a select number of countries. In support of this work and other analytical exercises, the OECD Statistics Directorate distributed a survey to all OECD countries on January 12, 2015 requesting information on the pension assets and liabilities of government sponsored pension schemes, as recorded both within and outside of the general government sector, as well as of government sponsored schemes not recorded in the national accounts. As of February 11, 2015, 16 of 34 countries have responded to the questionnaire. To facilitate a broader effort of achieving international comparability in pension statistics, the OECD Statistics Directorate and the IMF (to be confirmed) are planning to hold a pension workshop in the fall of The workshop will be similar to the workshop organised by the OECD and the Australian Bureau of Statistics in Australia in April 2013 and the workshop organised by Eurostat in Luxembourg in November The intention will be to discuss how to achieve international comparability in pension statistics and to exchange best practices in the estimation and recording of pensions more generally. Although a key item for discussion would be the extension of the platform to non-eu OECD countries, the participation of EU-countries, the ECB and Eurostat would be most

9 7 appreciated, in order to arrive at a better alignment of the conceptual and measurement issues, and also to benefit from the experience gained at the EU-level. At the workshop, the extent of required metadata to support the appropriate use of the data for policy analysis and research could also be considered. For further information, please contact Mr. Peter van de Ven (Peter.VANDEVEN@oecd.org) or Mr. Paul Goebel (Paul.GOEBEL@oecd.org) 4. Report Development of quantitative indicators of long-term investment finance To address the point made repeatedly during the G20 work on long-term investment finance that there is currently a shortage of readily accessible, consistent and comparable data on which to base policy analysis and conclusions, the staff of international organisations FSB, IMF, OECD and World Bank have initiated a project to develop a set of key quantitative indicators that summarise the main trends in the supply of and demand for long-term finance. These indicators would help to identify and monitor developments in long-term investment finance based on trends in volumes, maturities and costs broken down by funding destinations, instruments and sources of funds across both regions and time. The group has worked closely with a national engagement group of experts, which has provided evidence and analysis of a series of national use cases drawing on national data sources. Absent reliable information, there is a risk that policy recommendations are based on limited empirical support. Production of a stronger information base would provide a valuable foundation to underpin additional analysis and policy development in the area of long-term investment finance. Against this background, this report proposes a technical framework to assess data sources, takes stock of currently available data, and provides recommendations on next steps. 5. Quarterly Financial Sector Accounts In the framework of the recommendation 15 Sector Accounts - of the G-20 Data Gaps Initiative (DGI), the OECD Statistics Directorate (STD) collects data on Quarterly Financial Accounts and Financial Balance Sheets by institutional sector (households, government, financial corporations, non-financial corporations and the rest of the world) for all OECD countries, which follows the System of National Accounts S. Almost all OECD countries are now following the S 2008 methodology, except Chile, Japan and Turkey. These data, up to the third quarter of 2014, are available on the OECD data warehouse OECD.Stat ( as well as on the joint Principal Global Indicators website, hosted by the IMF ( For further information, please contact Ms. Isabelle Ynesta (Isabelle.ynesta@oecd.org). 6. Data collection on households assets and liabilities and on institutional investors assets The OECD Secretariat is redesigning its questionnaires on the institutional investors and households assets and liabilities data collection (tables T7II and T7HAL, respectively) to meet the key recommendations outlined in the report The Financial Crisis and Information Gaps, endorsed by the G-20 Finance Ministers and Central Bank Governors in November 2009, oriented to explore gaps and strengthening data collection, in particular, of non-bank financial institutions. This initiative is also intended to bring the classification breakdown of the financial sector and financial instruments in line with those recommended in the S2008 /ESA2010. It also includes a reflection on the data availability. At the last Working Party on Financial Statistics (WPFS) meeting in November 2014, the OECD Secretariat presented two proposals for each questionnaire (with different instrument and sector classification), and launched a survey just after the WPFS meeting with the aim of enquiring about the OECD countries preferences. Based on the results of the survey, the OECD is finalising the revision of these two questionnaires.

10 8 For further information, please contact M. Federico Giovannelli or Ms. Isabelle Ynesta 7. National Accounts at a Glance publication and the OECD Factbook The OECD publication National Accounts at a Glance (AG), created in 2009, presents information using an indicator approach, focusing on cross-country comparisons. The range of indicators, which is quite large, reflects the richness of the national accounts dataset. The focus goes well beyond GDP figures. Other important economic indicators, which may better respond to users needs and better measure economic performance and social progress of OECD economies, are well represented. In 2015, the paper version of this publication will be discontinued and the electronic version will be redesigned. The latter will include ten financial indicators of the OECD Financial Dashboard and will be released on the OECD data warehouse as well as on the new OECD data portal. For further information, please contact Ms. Jennifer Ribarsky (Jennifer.RIBARSKY@oecd.org). The OECD Factbook is the most comprehensive statistical publication of the OECD and is an essential tool to highlight key patterns of economic developments in all OECD countries. The 2015 edition will be released at the autumn and will contain three financial indicators selected in the OECD Financial Dashboard. General government debt, as a percentage of Gross Domestic Product (GDP) Households and NPISHs debt, as a percentage of Net Disposable Income (NDI) Composition of Households and NPISHs financial assets portfolio Concerning the general government debt-to-gdp ratio, for few OECD countries, such as Australia, Canada, Iceland, Sweden and the United States, which do record in the core accounts some unfunded liabilities of government employee pension plans in the general government debt data, an adjusted debt-to-gdp ratio will be calculated by excluding from the gross debt, these unfunded pension liabilities, allowing for a better comparability across OECD countries. Indeed, the status and treatment of government liabilities in respect of their employee pension plans in the national accounts is diverse across countries, making international comparability of government debts difficult. For further information, please contact Ms. Isabelle Ynesta (Isabelle.ynesta@oecd.org). 8. Memorandum of Understanding (MoU) and Service Level Agreement (SLA) between the European Central Bank (ECB) and the OECD in the area of National Accounts The MoU and the SLA between the ECB and the OECD in the area of national accounts have been finalised. They describe the agreed data exchange and data validation rules in the area of national accounts. The ECB will continue to provide the OECD with quarterly non-consolidated financial accounts data, both for euro area aggregates and for EU countries, both for stocks and for transactions. These data are produced under the responsibility of the Working Group of Euro Area Accounts. In counterpart, the OECD will transmit to the ECB annual and quarterly non-financial accounts, quarterly financial accounts, quarterly public sector debt data and unit labour costs for non-eu OECD countries. The technical features of the data exchange should follow the recommendations of the IAG Task Force on International Data Cooperation (TFIDC). Data will be transmitted by using the ESA2010/S2008 SDMX DSDs for national accounts codification (for the subset of national accounts data in the scope of this SLA, the _SEC DSD and _MAIN DSD should be used). The infrastructure used for the data exchange shall be efficient and reliable to minimize the burden to the Parties. Therefore, direct automated data transmissions via SDMX-ML messages shall be used by the Parties. For further information, please contact Ms. Isabelle Ynesta (Isabelle.ynesta@oecd.org).

11 9 9. Task Force on International Data Cooperation The Inter-Agency Group on Economic and Financial Statistics (IAG) has established a Task Force on International Data Cooperation (TFIDC) to examine the elements and undertake pilot exercises on a framework that would allow member countries of the agencies represented on the IAG to submit data only once, and for these data to be shared among the member agencies. All the seven international agencies are participating in this Task Force (International Monetary Fund, Bank for International Settlements, European Central Bank, Eurostat, OECD, United Nations and the World Bank). The overall objective of the TFIDC is to determine the procedures that could be applied for a successful data cooperation arrangement across international agencies that would streamline and improve the efficiency of data collection, sharing, and dissemination. To meet this objective, the TFIDC oversees two pilot exercises for (i) GDP main aggregates and population, and (ii) sector accounts. The first pilot exercise covers a set of main national accounts aggregates and auxiliary indicators that are widely used and are available for a large number of countries. It has started in September 2013 and should go live in Q with reference to Q data. It helped to set up and fine-tune the procedures using SDMX and National Accounts DSDs and to overcome the technical issues of data cooperation. The second pilot exercise will start in March 2015 and it will be based on the templates on sector accounts that have been developed by the Working Group on Sector Accounts and endorsed by the IAG. It will greatly benefit from the experience and the work done with the first pilot. For further information, please contact Ms. Rachida Dkhissi (Rachida.dkhissi@oecd.org). 10. Other work undertaken by the OECD Statistics Directorate in the context of the G20 DGI In the context of the recommendation 15 of the G-20 Data Gaps Initiative (DGI), the OECD Statistics Directorate (STD) collects data on Quarterly Non-Financial Accounts by institutional sector for all OECD countries and Key Partner countries, which follows in general the System of National Accounts 2008 S These data, up to the third quarter of 2014, are available on the OECD data warehouse OECD.Stat at the following address, as well as on the joint Principal Global Indicators website, hosted by the IMF ( For further information, please contact Ms. Rachida Dkhissi (Rachida.dkhissi@oecd.org). The joint Eurostat-OECD Task Force on Land and other Non-financial Assets is currently finalising its work on a compilation guide of land estimation. The compilation guide is expected to be published in March The primary purpose of this manual is to provide guidance in the compilation of estimates for the balance sheet item land. The impetus for the work of the Task Force is in response to the G20 Data Gaps Initiative recommendation 15. The concept of compiling national balance sheets for countries is not new, but there is increasing demand, also in view of the causes of the economic and financial crisis, for complete balance sheets of countries. Yet data, especially data on non-financial assets, total and by institutional sector, are often not available. Because of this, initially under the umbrella of the G20 DGI, a template had been developed for institutional sector accounts, among which minimum and encouraged stocks of nonfinancial assets by asset type and by sector. [1] This template has been discussed and agreed in various other groups (OECD Working Parties on Financial Statistics and National Accounts, Advisory Expert [1] IMF (2012-7), Templates for Minimum and Encouraged Set of Internationally Comparable Sectoral Accounts and Balance Sheets available at

12 10 Group on National Accounts). In response to interest on balance sheet data, the revised transmission programme for the European System of Integrated Economic Accounts (ESA 2010) also requires additional mandatory items for table 26 Balance sheets for non-financial assets. Most importantly the total value of land in the combined sector of households and non-profit institutions serving households (S.14 + S.15) are required for EU Member States to be transmitted to the European Commission (Eurostat) by In addition, the OECD collects information related to balance sheet items and is the primary data collector for non-european member countries of the OECD. For further information, please contact Ms. Jennifer Ribarsky (Jennifer.RIBARSKY@oecd.org). In addition to calculating and publishing the G20 aggregate for economic growth, the OECD Statistics Directorate has compiled and disseminated the G20-CPI. The OECD regularly releases the G20-CPI aggregate on a monthly basis, at around 35 days after the end of the reference period, following the release of national CPI and HICP data by all OECD and G20 countries. Consumer price indices (CPIs) measure inflation as price changes of a representative basket of goods and services typically purchased by households. The G20 CPI aggregate reflects national CPIs for all G20 countries that are not part of the European Union (EU) and reflects the Harmonised Indices of Consumer Prices (HICP) for the EU, its Member States and for Turkey. In March 2014, Argentinian authorities published a new national CPI (Indice de Precios al Consumidor Nacional urbano - IPCNu) which differs substantively from the preceding CPI (the CPI for the Greater Buenos Aires Area, CPI-GBA). The public release of the IPCNu was one of the specified actions in the IMF Executive Board s December 2013 decision calling on Argentina to address the quality of its official CPI data. Because of the differences in geographical coverage, weights, sampling and methodology, the IPCNu data cannot be directly compared to the earlier CPI-GBA data. Consequently, officially reported data for Argentina were excluded from January 2014 to November 2014 from the calculation of the annual percentage change of the G20 CPI aggregate. Detailed information is available at: For further information, please contact Ms. Anne-Sophie Fraisse (Anne-Sophie.FRAISSE@oecd.org). In line with recommendation 16 of the G20 Data Gaps Initiative, the OECD and Eurostat launched a joint Expert Group on Disparities in National Accounts (EG D) in 2011 to assess whether it is possible to devise an internationally comparable methodology to break down national accounts aggregates for the household sector using distributional information available from micro sources. Since then, the Expert Group has met four times and worked out a preliminary methodology to compile distributional results. Results from a first exercise using this methodology were already published, and provided a solid basis to further improve the methodology. At the April 2014 meeting of the Expert Group, it was decided to initiate a new exercise, focusing on a more recent year and updated methodology. The results will help the Expert Group to assess the robustness of the current methodology and will provide useful input for the work focusing on developing methodologies to compile more timely distributional estimates. The request was sent out in September of last year and member states were kindly asked to send their completed questionnaires by the end of March 2015 at the latest. In spring 2015, the fifth meeting of the Expert Group will be held. During this meeting, the results from the new exercise will be discussed and country experiences on the compilation process and problems encountered will be exchanged. Furthermore, the first ideas on the methodology for estimating more timely distributional information will be presented and discussed. For further information, please contact M. Jorrit Zwijnenburg (Jorrit.ZWIJNENBURG@oecd.org) In the context of the recommendation 19 Real Estate prices of the G-20 Data Gaps Initiative (DGI), the OECD Statistics Directorate aims to develop and give more visibility to house price

13 11 statistics for the 34 OECD countries and OECD accession and key partner countries. The collection of data on house price statistics for the OECD countries started during the first quarter of 2015 according to the roadmap proposed to the OECD Workshop on House Price Statistics held on March 24-25, This project is part of the CSTAT Programme of Work for that included an output result related to the development of house price statistics for OECD countries. In this context, the OECD s objective is to create an internationally comparable database focusing on House Price Indices (HPIs) - also called Residential Property Prices Indices (RPPIs) - and other associated indicators that provide a picture as complete as possible of the residential real estate market. In March 2014, the OECD Workshop on House Price Statistics was the opportunity 1) to present results of the OECD survey conducted in 2013 among the OECD countries to assess the availability of, and the methodology applied in measuring, house prices and other housing indicators; 2) to present issues and challenges that the OECD may face in developing a database with internationally comparable data for house prices and related indicators; 3) to arrive at defining a roadmap for the development of a database with internationally comparable data; and 4) to promote a research agenda for the further development of internationally comparable methods for compiling house price statistics. The discussions at the OECD Workshop of March 2014 indicated a broad consensus on 1) the preferred type of RPPI and 2) on the need to collect various related indicators that are useful to users of RPPIs. The target RPPI is an index that covers all dwellings; breakdowns should relate to the geographic dimension, dwelling vintage and type of property. The index should be based on actual transaction prices and be weighted according to relative transaction weights. Target frequency and timeliness of the price index should be quarterly, with releases within one quarter after the end of the reference period. Compilers are encouraged to cover other key housing indicators, including (but not limited to): house sales (existing and new dwellings), building permits, housing starts, vacancy rates, construction activity and land price indices. Based on these Workshop conclusions, the OECD has developed a framework for the collection of data to be included in the forthcoming OECD database on housing. This framework is organised around seven topics, covering house prices and other statistics aimed at better understanding the housing market situation in individual countries. The framework distinguishes between Tier 1 and Tier 2 items, with Tier 1 items having a higher priority and Tier 2 a lower priority in terms of data collection (see below). The collection of series included in Tier 1has started during the fourth quarter of For further information, please contact Ms. Anne-Sophie Fraisse (Anne-Sophie.FRAISSE@oecd.org).

14 12 OECD Framework on Housing Statistics I. Residential Property Price Indices (RPPI) I.1. Transaction based RPPI I.1.a. Transaction based RPPI for all dwellings I.1.b.Transaction based RPPI broken down by dwelling vintage Transaction based RPPI for new dwellings Transaction based RPPI for existing dwellings I.1.c. Transaction based RPPI broken down by geographical coverage Transaction based RPPI for capital citiy Transaction based RPPI for big cities (including capital city) Transaction based RPPI for rural areas 1.1.d. Transaction based RPPI broken down by type of property Transaction based RPPI for flats Transaction based RPPI for single family houses 1.1.e. Transaction based RPPI broken down by land and structures components Transaction based RPPI for land Transaction based RPPI for structures I.2. Stock based RPPI I.2.a. Stock based RPPI for all residential housing I.2.b. Stock based RPPI for owner occupied housing II. Other Housing price statistics II.1. CPI for housing II.1.a. CPI for Total housing II.1.b. CPI for Rented housing II.1.c. CPI for Owner occupied housing II.1.d. CPI for Maintenance and repair of the dwelling II.2. Median price statistics II.2.a. Median property prices (levels) II.2.b. Median price indices III. Residential property market III.1. Number of housing transactions III.1.a. Number of housing transactions - All vintages III.1.b. Number of housing transactions - New dwellings III.1.c. Number of housing transactions - Existing dwellings III.2. Value of housing transactions III.2.a. Value of housing transactions - All vintages III.2.b. Value of housing transactions - New dwellings III.2.c. Value of housing transactions - Existing dwellings Legend: Headline indicators (1st tier) / Additional indicators (2d tier)

15 13 ANNEX 1 OECD STATISTICS DIRECTORATE (STD) QUARTERLY PUBLIC SECTOR DEBT (QPSD) DATA COLLECTION TABLE 1. STATUS OF QPSD DATA COLLECTION TABLE 2. RESULTS OF THE SURVEY ON INSTRUMENT COVERAGE FOCUS ON THE GENERAL GOVERNMENT SECTOR

16 Table 1. Status of the quarterly Public Sector Debt data collection Public Sector Debt Sector coverage Valuation Consolidation International standards Australia Q Q S13; S1311; S11001; S12001; S1ZS Nominal Y S 2008 Austria Q Q S13; S1311; S1311B Face Y S 2008 Belgium Q Q S13; S1311 Face Y S 2008 Canada Q Q S13; S1311; S11001; S12001; S1ZS Nominal & book Y S 2008 Chile Q Q S1311B Face Y S 1993 Czech Republic Q Q S13; S1311; S1311B Face Y S 2008 Denmark Q Q S13; S1311 Nominal Y S 2008 Estonia Q Q S13; S1311 Nominal Y S 2008 Finland Q Q S13; S1311 Face Y S 2008 France Q Q S13; S1311 Face Y S 2008 Germany Q Q S13; S1311 Face Y S 2008 Greece Q Q S1311B Face Y S 2008 Hungary Q Q S13; S1311 Face Y S 2008 Iceland Q Q S1311; Face Y S 2008 Ireland Q Q S13; S1311; S1311B Face Y S 2008 Israel Q Q S1311 Nominal Y S 2008 Italy Q Q S13; S1311 Face Y S 2008 Japan Q Q S13; S1311; S11001; S12001 Market N S 1993 Korea 1 Q Q S13; S1311; S1311B; S11001; S1ZS Nominal Y S 2008 Luxembourg Q Q S13; S1311 Face Y S 2008 Mexico Q Q S13; S1311; S1311B; S11001; S12001;S1ZS Nominal Y S 2008 Netherlands Q Q S13; S1311; S1311B Face Y S 2008 New Zealand Q Q S1311 Market or present value Y IFRS Norway Q Q S13; S1311 Nominal Y S 2008 Poland Q Q S13; S1311; S1311B Nominal, market & face Y S 2008 Portugal Q Q S13; S1311; S11001 Face Y S 2008 Slovak Republic Q Q S13; S1311; S1311B; S1ZS Nominal Y S 2008 Slovenia Q Q S1311; S1311B Nominal Y S 1993 Spain Q Q S13; S1311; S1311B Face Y S 2008 Sweden Q Q S13; S1311 Nominal, book & face Y S 2008 Switzerland 1 Q Q S13; S1311 Face Y S 1993 Turkey Q Q S1311 Nominal N S 1993 United Kingdom Q Q S13; S1311; S11001 Face Y S 2008 United States Q Q S13; S1311 Book & nominal Y S 2008 Colombia Q Q S13; S1311; S1311B; S11001; S12001, S1ZS Nominal Y S 2008 Latvia Q Q S13; S1311 Face Y S 2008 Russia Q Q S1311? Y S Only annual data 14

17 15 Table 2. Results of the survey on debt instrument coverage Focus on the general government sector SDRs - AF12 AF2 - Currency & deposits AF3 - Debt securities AF4 - Loans AF6 - IPSGS AF8 - Other accounts payable Australia Austria =0 FC FC FC Data w ill be transmitted as from Q Data w ill be transmitted as from Q Belgium Liability of S121 FC FC FC ; but data exists ; but data exists Canada FC FC FC FC FC FC Chile 1 Data exists but cannot be ; but data exists FC FC ; but data exists ; but data exists reported Czech Republic Not applicable FC FC FC Not applicable FC Denmark =0 FC FC FC =0 FC Es tonia =0 =0 FC FC ; but data exists Data w ill be transmitted as from 2016 ; but data exists Data w ill be transmitted as from 2016 Finland =0 FC FC FC ; but data exists ; but data exists France FC=0 FC FC FC ; but data exists FC Germany =0 FC FC FC ; but data exists ; but data exists Greece 1 FC FC ; but data exists, but data exists Hungary Liability of S121 FC FC FC ; but data exists PC (only AF81) Iceland 2 Data recorded under S121 FC FC FC FC FC Ireland FC=0 FC FC FC FC FC Israel 2 Asset of S121 FC FC Italy Data recorded under S121 FC FC FC ; but data exists ; but data exists Japan FC FC FC FC Korea Data recorded under S121 =0 FC FC ; but data exists FC Luxembourg =0 FC FC FC ; but data exists ; but data exists Mexico =0 =0 FC FC =0 FC Netherlands Not applicable FC FC FC FC FC New Zealand 2 FC FC FC FC FC Norw ay =0 =0 FC FC =0 FC Poland Not applicable FC FC FC Portugal FC=0 FC FC FC FC=0 FC Slovak Republic FC=0 FC FC FC Not applicable FC Slovenia 2 FC FC FC FC Spain =0 Asset of S121 FC FC FC FC=0 FC Sw eden =0 Data recorded under S121 FC FC FC FC FC Sw itzerland =0 FC FC FC Data w ill be transmitted as from autumn 2015 Turkey 2 FC FC FC FC =0 ; but data exists United Kingdom FC FC FC FC =0 PC as from April 2015 FC United States FC FC FC FC PC Do not record standardised guarantees FC Colombia Latvia ; but data exists FC FC FC =0 Data w ill be transmitted as from April 2015 Russia 2 FC FC FC FC FC.. FC: Full coverage PC: Partial coverage : Data is not available =0: Data is not provided but equal to zero S121: Central Bank 1. Budgetary central government 2. Central government FC

18 16 C. OECD Directorate for Financial and Enterprise Affairs 1. OECD-Italian Treasury-World Bank Network for Supporting Sound Public Debt Management in Emerging Markets The OECD-Italian Treasury-World Bank Network for Public Debt Management in Emerging Markets is the result of a joint OECD-Italian initiative from 2002 and subsequently adopted by the OECD Working Party on Debt Management (WPDM). The World Bank joined the network as a partner in The Public Debt Management Network for Emerging Markets (PDM Network) is a virtual network ( that provides knowledge and information resources and a space for dialogue among debt managers and experts on public debt management and development and regulation of government securities markets. Established by the OECD and the Italian Treasury in cooperation with the OECD Working Party on Debt Management (WPDM), and in collaboration with the World Bank, the Network promotes knowledge sharing and exchange on sound practices in debt management, and provides data and information to support debt managers in their work. Through its website, the PDM Network offers partners free and protected access to documents, data sources, newsletters, and events. The Network also supports WPDM outreach activities, and contributes to the OECD Global Forum on Public Debt Management. PDM Network partners include governments, multilateral organizations, universities and research institutions. The Network continues to encourage participation of wider range of emerging market and developing countries. The PDM Network Governance Group acts as the Network steering group. It directs and plans the activities of the Network and oversees its work. The Governance Group is composed of representatives from the three Promoting Institutions (Italian Treasury, The OECD and the World Bank) and Members. Its size should not exceed 9 members. Promoting Institutions appoint permanent members, while Members participate on a rotational basis, for a period of two years in order to assure a gradual renewal and continuity. The composition of the Governance Group reflects the composition of the Network in terms of sovereign issuers, supranational or multilateral organisations and other Institutions. The Website of the Network plays therefore an important supporting role in executing the WPDM s outreach programme by diffusing in an efficient fashion the Working Party s pool of information, including statistics. The Network also contributes to the annual Global OECD Forum on Public Debt Management. 2 The Network is also a very useful tool to reduce some of the burden of bilateral contacts between OECD Debt Management Offices and their counter-parts from emerging markets, in particular by providing efficient access to information on OECD debt policies and bond market practices. A formal MOU was signed in A revised MOU (covering the participants as a partner by the World Bank) was signed in Its permanent Secretariat is based in the Italian Ministry of Finance [Romebased manager: Maria Cannata, Director General; (Maria.Cannata@tesoro.it). OECD manager: Hans Blommestein, (Hans.Blommestein@oecd.org). World Bank manager: Phillip Anderson, (prdanderson@worldbank.org) ] 2. The African Central Government Debt Statistical Yearbook. The OECD is also carrying out work on African public debt management and bond markets and has recently published a Statistical Yearbook on African Central Government Debt. For further information, please contact Mr. Hans Blommestein (Hans.Blommestein@oecd.org), Head of OECD s Public Debt 2 For example, the network organised a session on auctions in the 2005 Forum meeting, held in Amsterdam.

19 17 Management and Bond Market Unit and Chair of the Steering Committee of the Centre for African Public Debt Management and Bond Markets or Ms. Perla Ibarlucea Flores ) 3. The OECD Sovereign Borrowing Outlook. Each year, the OECD s Bond Market and Public Debt Management Unit circulates a survey on the borrowing needs of member governments. The responses are incorporated into the OECD Sovereign Borrowing Outlook to provide regular updates of trends and developments associated with sovereign borrowing requirements, funding strategies, market infrastructure and debt levels from the perspective of public debt managers. The Outlook makes a policy distinction between funding strategy and borrowing requirements. The central government marketable gross borrowing needs for the OECD area are calculated based on budget deficits and redemptions using a standard methodology. The funding strategy entails decisions on how these borrowing needs are financed using different instruments (e.g. long-term, shortterm, nominal, indexed) and on which distribution channels (e.g. auctions, tap, syndication) are being used. Accordingly, this Borrowing Outlook provides data, information and a background on sovereign borrowing needs, and discusses funding strategies and debt management policies for the OECD area and country groupings, by addressing the following issues: Gross borrowing requirements Net borrowing requirements The evolution of long-term rates Central government marketable debt Funding strategies and instruments For further information, please contact Mr. Hans Blommestein (Hans.Blommestein@oecd.org), Head of OECD s Public Debt Management and Bond Market Unit